Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "53"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 53 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 32 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 30 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 53, Node N03:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459848 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.253899 3.390257 -0.319367 0.671986 -0.615487 -0.450965 3.305232 6.357847 0.7391 0.7697 0.3805 3.222207 2.852897
2459846 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.245532 2.675333 -0.015419 0.261378 3.263371 0.989566 39.624800 18.438614 0.8562 0.7116 0.4661 3.087452 2.942563
2459845 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 3.524167 4.643750 -0.007541 0.168833 -0.687214 -0.524081 2.035038 4.205134 0.7488 0.7690 0.3735 0.000000 0.000000
2459844 digital_ok 100.00% 100.00% 100.00% 0.00% - - 29.744195 22.342269 21.174433 21.514016 4.962909 5.934105 7.880453 19.433955 0.0266 0.0244 0.0008 nan nan
2459843 digital_ok 100.00% 0.66% 0.66% 0.00% 100.00% 0.00% 2.478732 3.882097 -0.435240 -0.201959 1.267728 1.229135 2.716732 5.270628 0.7592 0.7682 0.3806 3.915411 3.654843
2459840 digital_ok 100.00% 100.00% 100.00% 0.00% - - 61.114539 41.937735 13.592522 13.509986 298.405514 332.375640 108.560225 123.089860 0.0244 0.0210 0.0012 nan nan
2459839 digital_ok 100.00% - - - - - 15.559011 10.393989 32.532496 32.916505 1.601750 2.238639 15.521482 21.365360 nan nan nan nan nan
2459838 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.119142 2.664564 -0.806091 0.441790 -1.090312 -0.417980 1.920342 5.973246 0.7698 0.7191 0.3929 4.576604 4.870216
2459836 digital_ok - 100.00% 100.00% 0.00% - - nan nan nan nan nan nan nan nan 0.0332 0.0325 0.0007 nan nan
2459835 digital_ok 100.00% 100.00% 100.00% 0.00% - - 0.335056 -0.247687 0.746040 0.578595 3.444294 4.393018 30.350521 37.095437 0.0327 0.0312 0.0012 nan nan
2459833 digital_ok 100.00% 100.00% 100.00% 0.00% - - 7.088712 4.971651 6.546878 6.826530 82.001078 93.006991 79.623504 97.128339 0.0273 0.0247 0.0011 nan nan
2459832 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.980860 2.573658 -0.952767 0.060579 -1.348331 -0.710867 2.439495 6.805370 0.8118 0.5583 0.5708 3.233321 2.915213
2459831 digital_ok 100.00% 100.00% 100.00% 0.00% - - 15.878274 11.132786 35.256449 35.540281 56.081877 62.092970 151.949630 171.672679 0.0241 0.0225 0.0008 nan nan
2459830 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.941020 2.972767 -0.947793 0.079171 -0.607993 0.161802 5.305963 12.839209 0.8108 0.5693 0.5517 5.201646 4.354181
2459829 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 3.883869 4.487640 -0.763500 0.207928 -0.151530 -0.884935 8.484933 17.226394 0.7689 0.6822 0.4051 6.943204 8.044259
2459828 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.331925 2.300723 -0.726692 0.000646 -0.607777 -0.439232 9.475584 17.965803 0.8083 0.5787 0.5340 3.608072 3.439011
2459827 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.920973 3.561489 -0.617399 0.265246 -0.543264 -0.092325 1.294163 4.469761 0.7765 0.6903 0.4081 13.891815 10.726306
2459826 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.293173 2.076123 -0.452757 0.048415 -0.637768 -0.105614 4.987265 16.653457 0.8071 0.6002 0.5106 6.871195 6.997181
2459825 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000
2459824 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.177114 3.154052 -0.619977 0.513486 -0.644795 -0.506446 3.728093 9.288236 0.7470 0.7479 0.3562 5.565241 5.123060
2459823 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.648223 1.608764 -0.469414 0.110027 -0.442356 -0.335190 5.215615 12.776737 0.7823 0.6643 0.4554 30.211795 14.042985
2459822 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 1.805352 1.920953 -0.660248 0.155250 -1.067511 -1.061840 1.043453 1.939725 0.8123 0.6384 0.4990 1.958439 1.750861
2459821 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 364.908661 365.187850 inf inf 711.512333 699.290323 1430.920903 1447.388300 nan nan nan 0.000000 0.000000
2459820 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.992822 3.398188 -0.682068 0.033535 0.426101 0.429821 4.164053 9.664999 0.7959 0.7241 0.3972 4.288812 4.283867
2459817 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 26.32% 1.260000 1.319019 -0.760450 -0.216778 -1.324259 -0.733770 0.453470 0.636527 0.8284 0.7108 0.4793 2.657914 2.454871
2459816 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000
2459815 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.398025 1.400413 -0.940438 -0.058122 -0.216182 0.782434 4.675129 12.384381 0.8225 0.7173 0.4878 3.817203 3.957941
2459814 digital_ok 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 4.354870 4.737765 -0.810646 -0.493884 0.330083 0.630892 8.054825 15.900722 0.8141 0.7706 0.3710 10.144842 6.047603

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 53: 2459848

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 6.357847 3.390257 2.253899 0.671986 -0.319367 -0.450965 -0.615487 6.357847 3.305232

Antenna 53: 2459846

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
53 N03 digital_ok ee Temporal Discontinuties 39.624800 2.245532 2.675333 -0.015419 0.261378 3.263371 0.989566 39.624800 18.438614

Antenna 53: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Shape 4.643750 4.643750 3.524167 0.168833 -0.007541 -0.524081 -0.687214 4.205134 2.035038

Antenna 53: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
53 N03 digital_ok ee Shape 29.744195 29.744195 22.342269 21.174433 21.514016 4.962909 5.934105 7.880453 19.433955

Antenna 53: 2459843

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 5.270628 3.882097 2.478732 -0.201959 -0.435240 1.229135 1.267728 5.270628 2.716732

Antenna 53: 2459840

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Variability 332.375640 61.114539 41.937735 13.592522 13.509986 298.405514 332.375640 108.560225 123.089860

Antenna 53: 2459839

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Power 32.916505 10.393989 15.559011 32.916505 32.532496 2.238639 1.601750 21.365360 15.521482

Antenna 53: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 5.973246 2.664564 2.119142 0.441790 -0.806091 -0.417980 -1.090312 5.973246 1.920342

Antenna 53: 2459835

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 37.095437 -0.247687 0.335056 0.578595 0.746040 4.393018 3.444294 37.095437 30.350521

Antenna 53: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 97.128339 4.971651 7.088712 6.826530 6.546878 93.006991 82.001078 97.128339 79.623504

Antenna 53: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 6.805370 2.980860 2.573658 -0.952767 0.060579 -1.348331 -0.710867 2.439495 6.805370

Antenna 53: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 171.672679 15.878274 11.132786 35.256449 35.540281 56.081877 62.092970 151.949630 171.672679

Antenna 53: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 12.839209 2.941020 2.972767 -0.947793 0.079171 -0.607993 0.161802 5.305963 12.839209

Antenna 53: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 17.226394 4.487640 3.883869 0.207928 -0.763500 -0.884935 -0.151530 17.226394 8.484933

Antenna 53: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 17.965803 2.300723 2.331925 0.000646 -0.726692 -0.439232 -0.607777 17.965803 9.475584

Antenna 53: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 4.469761 2.920973 3.561489 -0.617399 0.265246 -0.543264 -0.092325 1.294163 4.469761

Antenna 53: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 16.653457 2.076123 2.293173 0.048415 -0.452757 -0.105614 -0.637768 16.653457 4.987265

Antenna 53: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Shape nan nan nan inf inf nan nan nan nan

Antenna 53: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 9.288236 2.177114 3.154052 -0.619977 0.513486 -0.644795 -0.506446 3.728093 9.288236

Antenna 53: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 12.776737 1.608764 1.648223 0.110027 -0.469414 -0.335190 -0.442356 12.776737 5.215615

Antenna 53: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 1.939725 1.805352 1.920953 -0.660248 0.155250 -1.067511 -1.061840 1.043453 1.939725

Antenna 53: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Power inf 365.187850 364.908661 inf inf 699.290323 711.512333 1447.388300 1430.920903

Antenna 53: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 9.664999 2.992822 3.398188 -0.682068 0.033535 0.426101 0.429821 4.164053 9.664999

Antenna 53: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Shape 1.319019 1.260000 1.319019 -0.760450 -0.216778 -1.324259 -0.733770 0.453470 0.636527

Antenna 53: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Shape nan nan nan inf inf nan nan nan nan

Antenna 53: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 12.384381 1.400413 1.398025 -0.058122 -0.940438 0.782434 -0.216182 12.384381 4.675129

Antenna 53: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 53: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
53 N03 digital_ok nn Temporal Discontinuties 15.900722 4.737765 4.354870 -0.493884 -0.810646 0.630892 0.330083 15.900722 8.054825
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